Mark A. Davenport

117 papers A* 10A 3B 3Misc 10Journal 68Unranked 22

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LORE: Jointly Learning the Intrinsic Dimensionality and Relative Similarity Structure From Ordinal Data. CoRR Vivek Anand, Alec Helbling, Mark A. Davenport, Gordon J. Berman, Sankaraleengam Alagapan, Christopher John Rozell
2025	—	`conf`	A Fast Broadband Beamspace Transformation. CAMSAP Nakul Singh, Coleman DeLude, Mark A. Davenport, Justin Romberg
2025	J	`jnl`	Broadband Beamforming Using Low-Bit Precision Dimensionality Reduction. IEEE J. Sel. Top. Signal Process. Coleman DeLude, Xiangyu Mao, Sudarshan Sharma, Wei-Chun Wang, Saibal Mukhopadhyay, Mark A. Davenport, Justin Romberg
2025	J	`jnl`	Learning Sinkhorn Divergences for Change Point Detection. IEEE Trans. Signal Process. Nauman Ahad, Eva L. Dyer, Keith B. Hengen, Yao Xie, Mark A. Davenport
2025	A*	`conf`	SGD Jittering: A Training Strategy for Robust and Accurate Model-Based Architectures. ICML Peimeng Guan, Mark A. Davenport
2025	J	`jnl`	Test-Time Forward Model Adaptation for Seismic Deconvolution. IEEE Geosci. Remote. Sens. Lett. Peimeng Guan, Naveed Iqbal, Mark A. Davenport, Mudassir Masood
2025	J	`jnl`	Time Series Domain Adaptation via Channel-Selective Representation Alignment. Trans. Mach. Learn. Res. Nauman Ahad, Mark A. Davenport, Eva L. Dyer
2024	J	`jnl`	New Equivalences between Interpolation and SVMs: Kernels and Structured Features. SIAM J. Math. Data Sci. Chiraag Kaushik, Andrew D. McRae, Mark A. Davenport, Vidya Muthukumar
2024	J	`jnl`	Solving Inverse Problems with Model Mismatch using Untrained Neural Networks within Model-based Architectures. CoRR Peimeng Guan, Naveed Iqbal, Mark A. Davenport, Mudassir Masood
2024	J	`jnl`	Solving Inverse Problems with Model Mismatch using Untrained Neural Networks within Model-based Architectures. Trans. Mach. Learn. Res. Peimeng Guan, Naveed Iqbal, Mark A. Davenport, Mudassir Masood
2024	J	`jnl`	Stochastic Gradient Descent Jittering for Inverse Problems: Alleviating the Accuracy-Robustness Tradeoff. CoRR Peimeng Guan, Mark A. Davenport
2023	A	`conf`	Active metric learning and classification using similarity queries. UAI Namrata Nadagouda, Austin Xu, Mark A. Davenport
2023	J	`jnl`	Distance preservation in state-space methods for detecting causal interactions in dynamical systems. CoRR Matthew R. O'Shaughnessy, Mark A. Davenport, Christopher Rozell
2023	J	`jnl`	Iterative Broadband Source Localization. IEEE J. Sel. Areas Inf. Theory Coleman DeLude, Rakshith Sharma Srinivasa, Santhosh Karnik, Christopher Hood, Mark A. Davenport, Justin Romberg
2023	J	`jnl`	New Equivalences Between Interpolation and SVMs: Kernels and Structured Features. CoRR Chiraag Kaushik, Andrew D. McRae, Mark A. Davenport, Vidya Muthukumar
2023	J	`jnl`	Optimal Convex Lifted Sparse Phase Retrieval and PCA With an Atomic Matrix Norm Regularizer. IEEE Trans. Inf. Theory Andrew D. McRae, Justin Romberg, Mark A. Davenport
2023	A*	`conf`	Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning. NeurIPS Austin Xu, Andrew D. McRae, Jingyan Wang, Mark A. Davenport, Ashwin Pananjady
2023	J	`jnl`	Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning. CoRR Austin Xu, Andrew D. McRae, Jingyan Wang, Mark A. Davenport, Ashwin Pananjady
2022	J	`jnl`	Active metric learning and classification using similarity queries. CoRR Namrata Nadagouda, Austin Xu, Mark A. Davenport
2022	Misc	`conf`	Delta Distancing: A Lifting Approach to Localizing Items from User Comparisons. ICASSP Andrew D. McRae, Austin Xu, Jihui Jin, Namrata Nadagouda, Nauman Ahad, Peimeng Guan, Santhosh Karnik, Mark A. Davenport
2022	A	`conf`	Harmless interpolation in regression and classification with structured features. AISTATS Andrew D. McRae, Santhosh Karnik, Mark A. Davenport, Vidya K. Muthukumar
2022	J	`jnl`	Learning Sinkhorn divergences for supervised change point detection. CoRR Nauman Ahad, Eva L. Dyer, Keith B. Hengen, Yao Xie, Mark A. Davenport
2022	J	`jnl`	Loop Unrolled Shallow Equilibrium Regularizer (LUSER) - A Memory-Efficient Inverse Problem Solver. CoRR Peimeng Guan, Jihui Jin, Justin Romberg, Mark A. Davenport
2022	J	`jnl`	Thomson's Multitaper Method Revisited. IEEE Trans. Inf. Theory Santhosh Karnik, Justin Romberg, Mark A. Davenport
2021	J	`jnl`	As You Like It: Localization via Paired Comparisons. J. Mach. Learn. Res. Andrew K. Massimino, Mark A. Davenport
2021	A*	`conf`	Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time. NeurIPS Feng Zhu, Andrew R. Sedler, Harrison A. Grier, Nauman Ahad, Mark A. Davenport, Matthew T. Kaufman, Andrea Giovannucci, Chethan Pandarinath
2021	J	`jnl`	Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time. CoRR Feng Zhu, Andrew R. Sedler, Harrison A. Grier, Nauman Ahad, Mark A. Davenport, Matthew T. Kaufman, Andrea Giovannucci, Chethan Pandarinath
2021	J	`jnl`	Harmless interpolation in regression and classification with structured features. CoRR Andrew D. McRae, Santhosh Karnik, Mark A. Davenport, Vidya Muthukumar
2021	A*	`conf`	Semi-supervised Sequence Classification through Change Point Detection. AAAI Nauman Ahad, Mark A. Davenport
2021	Misc	`conf`	Switched Hawkes Processes. ICASSP Namrata Nadagouda, Mark A. Davenport
2021	J	`jnl`	Thomson's Multitaper Method Revisited. CoRR Santhosh Karnik, Justin Romberg, Mark A. Davenport
2020	Misc	`conf`	Active Embedding Search via Noisy Paired Comparisons. ITA Gregory H. Canal, Andrew K. Massimino, Mark A. Davenport, Christopher J. Rozell
2020	J	`jnl`	Audio-Based Bayesian Model for Productivity Estimation of Cyclic Construction Activities. J. Comput. Civ. Eng. Chris Sabillon, Abbas Rashidi, Biswanath Samanta, Mark A. Davenport, David V. Anderson
2020	B	`conf`	Dynamic Knowledge Embedding and Tracing. EDM Liangbei Xu, Mark A. Davenport
2020	J	`jnl`	Dynamic Knowledge embedding and tracing. CoRR Liangbei Xu, Mark A. Davenport
2020	A*	`conf`	Generative causal explanations of black-box classifiers. NeurIPS Matthew R. O'Shaughnessy, Gregory Canal, Marissa Connor, Christopher Rozell, Mark A. Davenport
2020	J	`jnl`	Generative causal explanations of black-box classifiers. CoRR Matthew R. O'Shaughnessy, Gregory Canal, Marissa Connor, Mark A. Davenport, Christopher Rozell
2020	J	`jnl`	Localized sketching for matrix multiplication and ridge regression. CoRR Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg
2020	A*	`conf`	Sample complexity and effective dimension for regression on manifolds. NeurIPS Andrew D. McRae, Justin Romberg, Mark A. Davenport
2020	J	`jnl`	Sample complexity and effective dimension for regression on manifolds. CoRR Andrew D. McRae, Justin Romberg, Mark A. Davenport
2020	A	`conf`	Sample complexity bounds for localized sketching. AISTATS Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg
2020	J	`jnl`	Semi-supervised sequence classification through change point detection. CoRR Nauman Ahad, Mark A. Davenport
2020	A*	`conf`	Simultaneous Preference and Metric Learning from Paired Comparisons. NeurIPS Austin Xu, Mark A. Davenport
2020	J	`jnl`	Simultaneous Preference and Metric Learning from Paired Comparisons. CoRR Austin Xu, Mark A. Davenport
2020	J	`jnl`	Sparse Bayesian Learning With Dynamic Filtering for Inference of Time-Varying Sparse Signals. IEEE Trans. Signal Process. Matthew R. O'Shaughnessy, Mark A. Davenport, Christopher J. Rozell
2020	Misc	`conf`	The Picasso Algorithm for Bayesian Localization Via Paired Comparisons in a Union of Subspaces Model. ICASSP Gregory Canal, Marissa Connor, Jihui Jin, Namrata Nadagouda, Matthew R. O'Shaughnessy, Christopher J. Rozell, Mark A. Davenport
2020	J	`jnl`	Trading Beams for Bandwidth: Imaging with Randomized Beamforming. SIAM J. Imaging Sci. Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg
2019	A*	`conf`	Active Embedding Search via Noisy Paired Comparisons. ICML Gregory Canal, Andrew K. Massimino, Mark A. Davenport, Christopher J. Rozell
2019	J	`jnl`	Active embedding search via noisy paired comparisons. CoRR Gregory H. Canal, Andrew K. Massimino, Mark A. Davenport, Christopher J. Rozell
2019	J	`jnl`	Correction to: On the Stability and Accuracy of Least Squares Approximations. Found. Comput. Math. Albert Cohen, Mark A. Davenport, Dany Leviatan
2019	—	`conf`	Dynamical System Implementations of Sparse Bayesian Learning. CAMSAP Matthew R. O'Shaughnessy, Mark A. Davenport, Christopher J. Rozell
2019	J	`jnl`	Estimation of Poisson Arrival Processes Under Linear Models. IEEE Trans. Inf. Theory Michael G. Moore, Mark A. Davenport
2019	—	`conf`	Joint Estimation of Trajectory and Dynamics from Paired Comparisons. CAMSAP Gregory H. Canal, Matthew R. O'Shaughnessy, Christopher J. Rozell, Mark A. Davenport
2019	J	`jnl`	Low-rank matrix completion and denoising under Poisson noise. CoRR Andrew D. McRae, Mark A. Davenport
2018	J	`jnl`	A Unified Framework for Manifold Landmarking. IEEE Trans. Signal Process. Hongteng Xu, Licheng Yu, Mark A. Davenport, Hongyuan Zha
2018	—	`conf`	Approximating Cellular Densities from High-Resolution Neuroanatomical Imaging Data. EMBC Theodore J. LaGrow, Michael G. Moore, Judy A. Prasad, Mark A. Davenport, Eva L. Dyer
2018	J	`jnl`	As you like it: Localization via paired comparisons. CoRR Andrew K. Massimino, Mark A. Davenport
2018	—	`conf`	Audio Classification Based on Weakly Labeled Data. SSP Chieh-Feng Cheng, David V. Anderson, Mark A. Davenport, Abbas Rashidi
2018	J	`jnl`	Estimation of Poisson arrival processes under linear models. CoRR Michael G. Moore, Mark A. Davenport
2018	—	`conf`	Localized random projections with applications to coherent array imaging. Allerton Rakshith Sharma Srinivasa, Mark A. Davenport, Justin Romberg
2018	J	`jnl`	ROAST: Rapid Orthogonal Approximate Slepian Transform. IEEE Trans. Signal Process. Zhihui Zhu, Santhosh Karnik, Michael B. Wakin, Mark A. Davenport, Justin Romberg
2018	J	`jnl`	The Eigenvalue Distribution of Discrete Periodic Time-Frequency Limiting Operators. IEEE Signal Process. Lett. Zhihui Zhu, Santhosh Karnik, Mark A. Davenport, Justin Romberg, Michael B. Wakin
2017	J	`jnl`	Active manifold learning via a unified framework for manifold landmarking. CoRR Hongteng Xu, Licheng Yu, Mark A. Davenport, Hongyuan Zha
2017	Misc	`conf`	Fast orthogonal approximations of sampled sinusoids and bandlimited signals. ICASSP Zhihui Zhu, Santhosh Karnik, Michael B. Wakin, Mark A. Davenport, Justin K. Romberg
2017	J	`jnl`	ROAST: Rapid Orthogonal Approximate Slepian Transform. CoRR Zhihui Zhu, Santhosh Karnik, Michael B. Wakin, Mark A. Davenport, Justin Romberg
2017	—	`conf`	Simultaneous recovery of a series of low-rank matrices by locally weighted matrix smoothing. CAMSAP Liangbei Xu, Mark A. Davenport
2017	J	`jnl`	The Eigenvalue Distribution of Discrete Periodic Time-Frequency Limiting Operators. CoRR Zhihui Zhu, Santhosh Karnik, Mark A. Davenport, Justin Romberg, Michael B. Wakin
2017	Misc	`conf`	The geometry of random paired comparisons. ICASSP Andrew K. Massimino, Mark A. Davenport
2016	—	`conf`	A Hawkes' eye view of network information flow. SSP Michael G. Moore, Mark A. Davenport
2016	J	`jnl`	An Overview of Low-Rank Matrix Recovery From Incomplete Observations. IEEE J. Sel. Top. Signal Process. Mark A. Davenport, Justin K. Romberg
2016	J	`jnl`	An overview of low-rank matrix recovery from incomplete observations. CoRR Mark A. Davenport, Justin K. Romberg
2016	—	`conf`	Analysis of wireless networks using Hawkes processes. SPAWC Michael G. Moore, Mark A. Davenport
2016	—	`conf`	Binary stable embedding via paired comparisons. SSP Andrew K. Massimino, Mark A. Davenport
2016	J	`jnl`	Constrained Adaptive Sensing. IEEE Trans. Signal Process. Mark A. Davenport, Andrew K. Massimino, Deanna Needell, Tina Woolf
2016	—	`conf`	Dynamic matrix recovery from incomplete observations under an exact low-rank constraint. NIPS Liangbei Xu, Mark A. Davenport
2016	J	`jnl`	Dynamic matrix recovery from incomplete observations under an exact low-rank constraint. CoRR Liangbei Xu, Mark A. Davenport
2016	—	`conf`	Fast computations for approximation and compression in Slepian spaces. GlobalSIP Santhosh Karnik, Zhihui Zhu, Michael B. Wakin, Justin K. Romberg, Mark A. Davenport
2016	—	`conf`	Localizing users and items from paired comparisons. MLSP Matthew R. O'Shaughnessy, Mark A. Davenport
2015	A*	`conf`	Active Manifold Learning via Gershgorin Circle Guided Sample Selection. AAAI Hongteng Xu, Hongyuan Zha, Ren-Cang Li, Mark A. Davenport
2015	J	`jnl`	Constrained adaptive sensing. CoRR Mark A. Davenport, Andrew K. Massimino, Deanna Needell, Tina Woolf
2015	—	`conf`	Randomized multi-pulse time-of-flight mass spectrometry. CAMSAP Michael G. Moore, Andrew K. Massimino, Mark A. Davenport
2014	A*	`conf`	Manifold Based Dynamic Texture Synthesis from Extremely Few Samples. CVPR Hongteng Xu, Hongyuan Zha, Mark A. Davenport
2014	J	`jnl`	Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection. IEEE Signal Process. Mag. Rebecca M. Willett, Marco F. Duarte, Mark A. Davenport, Richard G. Baraniuk
2013	Misc	`conf`	Cleaning up toxic waste: Removing nefarious contributions to recommendation systems. ICASSP Adam Charles, Ali Ahmed, Aditya Joshi, Stephen Conover, Christopher K. Turnes, Mark A. Davenport
2013	—	`conf`	Lost without a compass: Nonmetric triangulation and landmark multidimensional scaling. CAMSAP Mark A. Davenport
2013	B	`conf`	Lower bounds for quantized matrix completion. ISIT Mary Wootters, Yaniv Plan, Mark A. Davenport, Ewout van den Berg
2013	J	`jnl`	On the Fundamental Limits of Adaptive Sensing. IEEE Trans. Inf. Theory Ery Arias-Castro, Emmanuel J. Candès, Mark A. Davenport
2013	J	`jnl`	On the Stability and Accuracy of Least Squares Approximations. Found. Comput. Math. Albert Cohen, Mark A. Davenport, Dany Leviatan
2013	J	`jnl`	Signal Space CoSaMP for Sparse Recovery With Redundant Dictionaries. IEEE Trans. Inf. Theory Mark A. Davenport, Deanna Needell, Michael B. Wakin
2012	J	`jnl`	1-Bit Matrix Completion CoRR Mark A. Davenport, Yaniv Plan, Ewout van den Berg, Mary Wootters
2012	Misc	`conf`	A compressive phase-locked loop. ICASSP Stephen R. Schnelle, John P. Slavinsky, Petros Boufounos, Mark A. Davenport, Richard G. Baraniuk
2012	—	`conf`	CoSaMP with redundant dictionaries. ACSCC Mark A. Davenport, Deanna Needell, Michael B. Wakin
2012	J	`jnl`	Compressive binary search CoRR Mark A. Davenport, Ery Arias-Castro
2012	B	`conf`	Compressive binary search. ISIT Mark A. Davenport, Ery Arias-Castro
2012	—	`ch.`	Introduction to compressed sensing. Compressed Sensing Mark A. Davenport, Marco F. Duarte, Yonina C. Eldar, Gitta Kutyniok
2012	J	`jnl`	Signal Space CoSaMP for Sparse Recovery with Redundant Dictionaries CoRR Mark A. Davenport, Deanna Needell, Michael B. Wakin
2012	J	`jnl`	The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding versus Dynamic Range. IEEE Trans. Signal Process. Mark A. Davenport, Jason N. Laska, John R. Treichler, Richard G. Baraniuk
2011	J	`jnl`	Compressive Sensing of Analog Signals Using Discrete Prolate Spheroidal Sequences CoRR Mark A. Davenport, Michael B. Wakin
2011	J	`jnl`	How well can we estimate a sparse vector? CoRR Emmanuel J. Candès, Mark A. Davenport
2011	J	`jnl`	On the Fundamental Limits of Adaptive Sensing CoRR Ery Arias-Castro, Emmanuel J. Candès, Mark A. Davenport
2011	J	`jnl`	The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic Range CoRR Mark A. Davenport, Jason N. Laska, John R. Treichler, Richard G. Baraniuk
2011	Misc	`conf`	The compressive multiplexer for multi-channel compressive sensing. ICASSP John P. Slavinsky, Jason N. Laska, Mark A. Davenport, Richard G. Baraniuk
2010	J	`jnl`	Analysis of orthogonal matching pursuit using the restricted isometry property. IEEE Trans. Inf. Theory Mark A. Davenport, Michael B. Wakin
2010	—	`conf`	High Dimensional Data Fusion via Joint Manifold Learning. AAAI Fall Symposium: Manifold Learning and Its Applications Mark A. Davenport, Chinmay Hegde, Marco F. Duarte, Richard G. Baraniuk
2010	J	`jnl`	Joint Manifolds for Data Fusion. IEEE Trans. Image Process. Mark A. Davenport, Chinmay Hegde, Marco F. Duarte, Richard G. Baraniuk
2010	J	`jnl`	Signal Processing With Compressive Measurements. IEEE J. Sel. Top. Signal Process. Mark A. Davenport, Petros Boufounos, Michael B. Wakin, Richard G. Baraniuk
2010	Misc	`conf`	Texas Hold 'Em algorithms for distributed compressive sensing. ICASSP Stephen R. Schnelle, Jason N. Laska, Chinmay Hegde, Marco F. Duarte, Mark A. Davenport, Richard G. Baraniuk
2010	J	`jnl`	Tuning Support Vector Machines for Minimax and Neyman-Pearson Classification. IEEE Trans. Pattern Anal. Mach. Intell. Mark A. Davenport, Richard G. Baraniuk, Clayton D. Scott
2009	J	`jnl`	A Theoretical Analysis of Joint Manifolds CoRR Mark A. Davenport, Chinmay Hegde, Marco F. Duarte, Richard G. Baraniuk
2009	J	`jnl`	A simple proof that random matrices are democratic CoRR Mark A. Davenport, Jason N. Laska, Petros Boufounos, Richard G. Baraniuk
2009	—	`conf`	Sparse Geodesic Paths. AAAI Fall Symposium: Manifold Learning and Its Applications Mark A. Davenport, Richard G. Baraniuk
2008	J	`jnl`	Single-pixel imaging via compressive sampling. IEEE Signal Process. Mag. Marco F. Duarte, Mark A. Davenport, Dharmpal Takhar, Jason N. Laska, Ting Sun, Kevin F. Kelly, Richard G. Baraniuk
2007	—	`conf`	Multiscale Random Projections for Compressive Classification. ICIP (6) Marco F. Duarte, Mark A. Davenport, Michael B. Wakin, Jason N. Laska, Dharmpal Takhar, Kevin F. Kelly, Richard G. Baraniuk
2007	J	`jnl`	Regression Level Set Estimation Via Cost-Sensitive Classification. IEEE Trans. Signal Process. Clayton D. Scott, Mark A. Davenport
2007	—	`conf`	The smashed filter for compressive classification and target recognition. Computational Imaging Mark A. Davenport, Marco F. Duarte, Michael B. Wakin, Jason N. Laska, Dharmpal Takhar, Kevin F. Kelly, Richard G. Baraniuk
2006	—	`conf`	Controlling False Alarms With Support Vector Machines. ICASSP (5) Mark A. Davenport, Richard G. Baraniuk, Clayton D. Scott
2006	—	`conf`	Sparse Signal Detection from Incoherent Projections. ICASSP (3) Marco F. Duarte, Mark A. Davenport, Michael B. Wakin, Richard G. Baraniuk